LLM Reference

Code Cushman 001 vs Llama 3.1 405B Instruct

Code Cushman 001 (2021) and Llama 3.1 405B Instruct (2024) compare a coding-specialized model against a standalone API model. Code Cushman 001 ships a not-yet-sourced context window, while Llama 3.1 405B Instruct ships a 128k-token context window. This page treats the result as workflow and deployment fit, not a universal model winner.

Treat this as a product-type comparison: Code Cushman 001 is coding-specialized model, while Llama 3.1 405B Instruct is standalone API model. Choose based on workflow fit before reading any benchmark or price row as decisive.

Decision scorecard

Local evidence first
SignalCode Cushman 001Llama 3.1 405B Instruct
Product typeCoding-specialized modelStandalone API model
Best forcustom coding agents and code generationprovider-routed production
Decision fitCodingRAG, Long context, and Classification
Context window128k
Cheapest output-$2.40/1M tokens
Provider routes0 tracked11 tracked
Shared benchmarks0 rows0 rows

Decision tradeoffs

Choose Code Cushman 001 when...
  • Local decision data tags Code Cushman 001 for Coding.
Choose Llama 3.1 405B Instruct when...
  • Llama 3.1 405B Instruct has the larger context window for long prompts, retrieval packs, or transcript analysis.
  • Llama 3.1 405B Instruct has broader tracked provider coverage for fallback and procurement flexibility.
  • Llama 3.1 405B Instruct uniquely exposes Structured outputs in local model data.
  • Local decision data tags Llama 3.1 405B Instruct for RAG, Long context, and Classification.

Monthly cost at traffic

Estimate token spend from the cheapest tracked input and output route or tier on this page.

Code Cushman 001

Unavailable

No complete token price in local provider data

Llama 3.1 405B Instruct

$2,520

Cheapest tracked route/tier: AWS Bedrock

Cost delta unavailable until both models have sourced input and output token prices.

Switch friction

Code Cushman 001 -> Llama 3.1 405B Instruct
  • No overlapping tracked provider route is sourced for Code Cushman 001 and Llama 3.1 405B Instruct; plan for SDK, billing, or endpoint changes.
  • Llama 3.1 405B Instruct adds Structured outputs in local capability data.
Llama 3.1 405B Instruct -> Code Cushman 001
  • No overlapping tracked provider route is sourced for Llama 3.1 405B Instruct and Code Cushman 001; plan for SDK, billing, or endpoint changes.
  • Check replacement coverage for Structured outputs before moving production traffic.

Specs

Specification
Released2021-11-032024-07-23
Context window128k
Parameters405B
Architecturedecoder onlydecoder only
LicenseProprietaryLlama 3 Community
OpennessProprietaryOpen weights
Commercial useCommercial use with conditionsCommercial use with conditions
Knowledge cutoff-2023-12

Pricing and availability

Pricing attributeCode Cushman 001Llama 3.1 405B Instruct
Input price-$2.40/1M tokens
Output price-$2.40/1M tokens
Providers-

Capabilities

CapabilityCode Cushman 001Llama 3.1 405B Instruct
VisionNoNo
MultimodalNoNo
ReasoningNoNo
Function callingNoNo
Tool useNoNo
Structured outputsNoYes
Code executionNoNo
IDE integrationNoNo
Computer useNoNo
Parallel agentsNoNo

Benchmarks

No shared benchmark rows are currently sourced for this pair.

Deep dive

The capability footprint differs most on structured outputs: Llama 3.1 405B Instruct. Both models share the core language-model surface, so the practical split is not just feature count. Use those differences to decide whether the page is about raw model quality, agentic coding support, multimodal ingestion, or predictable structured API behavior.

Pricing coverage is uneven: Code Cushman 001 has no token price sourced yet and Llama 3.1 405B Instruct has $2.40/1M input tokens. Provider availability is 0 tracked routes versus 11. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.

Choose Code Cushman 001 when coding workflow support are central to the workload. Choose Llama 3.1 405B Instruct when provider fit and broader provider choice are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship. This keeps the decision grounded in measurable tradeoffs instead of brand-level assumptions. It also helps separate model capability from provider packaging, which can change cost and latency. For teams standardizing a stack, that distinction is often the difference between a benchmark win and a reliable deployment.

FAQ

Is Code Cushman 001 or Llama 3.1 405B Instruct open source?

Code Cushman 001 is listed under Proprietary. Llama 3.1 405B Instruct is listed under Llama 3 Community. License labels affect whether you can self-host, redistribute weights, or rely only on hosted APIs, so confirm the upstream license before deployment.

Which is better for structured outputs, Code Cushman 001 or Llama 3.1 405B Instruct?

Llama 3.1 405B Instruct has the clearer documented structured outputs signal in this comparison. If structured outputs is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.

Where can I run Code Cushman 001 and Llama 3.1 405B Instruct?

Code Cushman 001 is available on the tracked providers still being sourced. Llama 3.1 405B Instruct is available on OctoAI API (Deprecated), Together AI, Fireworks AI, IBM watsonx, and Scale AI GenAI Platform. Provider coverage can affect latency, region availability, compliance posture, and fallback options.

When should I pick Code Cushman 001 over Llama 3.1 405B Instruct?

Treat this as a product-type comparison: Code Cushman 001 is coding-specialized model, while Llama 3.1 405B Instruct is standalone API model. Choose based on workflow fit before reading any benchmark or price row as decisive. If your workload also depends on coding workflow support, start with Code Cushman 001; if it depends on provider fit, run the same evaluation with Llama 3.1 405B Instruct.

Continue comparing

Last reviewed: 2026-05-16. Data sourced from public model cards and provider documentation.